Driver Speed Profiles Index Warning Signs of MCI

Abstract Goal Use driver behavior profiles to screen and index early warnings of cognitive decline and Alzheimer’s disease (AD). Hypothesis: Real-world driver speed behavior profiles discriminate mild cognitive impairment (MCI). Methods Sensors were installed in personal vehicles of 74 legally-licensed, active drivers (age: 65-90 years, μ = 75.85) who completed 2, 3-month real-world driving assessments, including demographic and cognitive assessments, 1 year apart (244,564 miles driven). MCI status was indexed using 8 neuropsychological tests (spanning executive function, visuospatial skills, processing speed, and memory), relevant to MCI and driving. Driving environment was indexed from state speed limit (SL; roadway type: residential, commercial, interstate) and sunrise-sunset databases (time of day: day vs. night). Models: Data were randomly split into training (66%) and validation (33%) sets. An optimal mixed effects logistic regression model was determined from validation data AUC values. Results MCI drivers drove slower with optimal discrimination (estimated for every 5 mph decrease in speeding) in 1) residential roads (SL 25-35 mph; MCI odds increased by 6% [95% CI: 2-11%]), 2) interstate roads (SL >55 mph; MCI odds increased by 14% [95% CI: 8-20%]), and 3) night environments (MCI odds increased by 7% [95% CI: 2-12%]). Conclusion Quantitative indices of real-world driver data provide “ground truth” for screening and indexing phenotypes of cognitive decline, in line with ongoing efforts to link driver behavior with age-related cognitive decline and AD biomarkers. Behavioral biomarkers for diagnosing early warnings of dementia could ultimately bolster our ability to detect and intervene in early AD.

Informal caregivers often provide transportation assistance as older adult care recipients (CRs) begin regulating their driving (e.g., avoid certain driving situations, decrease/ cease driving). This study examined how caregiver and CR driving frequency and CR's driving avoidance behaviors impact caregiving intensity. Using data from Round 7 of the National Health and Aging Trends Study and the linked National Survey of Caregiving (n=1048 dyads), results indicated that caregiving intensity was highest among caregivers who drove everyday (5.38 hours) and for CRs who had not driven in the last month/did not drive (4.65 hours). Negative binomial regression techniques were used to assess and compare driving-related predictors. Compared to CRs who reported no avoidance of nighttime driving, caregivers of CRs who do not drive at all can expect to provide about 36% more hours of caregiving per day. Caregiving intensity was not significantly related to CR's driving alone, on the highway, or in bad weather avoidance behaviors. CRs who drove every day, most days, and rarely required between 33% and 40% fewer expected hours per day of caregiving compared to CRs who had not driven in the past month. The expected number of hours spent providing care per day was 36% higher among caregivers who drove the care recipient every day, 28% higher among most-day drivers, and 30% higher among those who never drove as opposed to caregivers who drove some days per week. Results suggest that caregiving intensity is related more to caregiver and CR driving frequency than CR driving avoidance behaviors.

CHANGES IN TRANSPORTATION DURING THE COVID-19 PANDEMIC: RESULTS FROM A SURVEY OF MIDDLE-AGED AND OLDER FLORIDIANS
Anne Barrett, Cherish Michael, and Jessica Noblitt, Florida State University, Tallahassee, Florida, United States The pandemic's numerous effects on everyday life include reductions in driving and changes in the use of other transportation modes, like getting rides from family and friends, walking, and biking. Aside from broad patterns, however, little is known about these changes, including how they affected different groups of the population and how they felt about them. Our study addresses these issues using data collected from an online survey of over 4,000 Floridians aged 50 or older, conducted between December 2020 and April 2021 and funded by the Florida Department of Transportation to support its aging road user program, Safe Mobility for Life. Changes in driving and in rides from family and friends were more striking than those in other transportation modes. Nearly 30 percent of respondents decreased their driving during the pandemic, while 20 percent got fewer rides from family and 25 percent got fewer rides from friends. In contrast, only 11 percent decreased their walking, and the same percentage increased it. Less common were changes in biking, with percent 7 decreasing and only 4 percent increasing it. Multivariate analyses revealed that these changes were influenced by gender, race, age, socioeconomic status, and health. Further insight was gained from analysis of an open-ended item, revealing positive and negative assessments of the changes. Positive assessments centered on feeling satisfied with working at home, spending more time outdoors, having more free time, and saving money. Negative assessments centered on social isolation, dissatisfaction with government responses to the pandemic, and reduced transportation options. Goal: Use driver behavior profiles to screen and index early warnings of cognitive decline and Alzheimer's disease (AD). Hypothesis: Real-world driver speed behavior profiles discriminate mild cognitive impairment (MCI).

DRIVER SPEED PROFILES INDEX WARNING SIGNS OF MCI
Methods:Sensors were installed in personal vehicles of 74 legally-licensed, active drivers (age: 65-90 years, μ = 75.85) who completed 2, 3-month real-world driving assessments, including demographic and cognitive assessments, 1 year apart (244,564 miles driven). MCI status was indexed using 8 neuropsychological tests (spanning executive function, visuospatial skills, processing speed, and memory), relevant to MCI and driving. Driving environment was indexed from state speed limit (SL; roadway type: residential, commercial, interstate) and sunrise-sunset databases (time of day: day vs. night). Models: Data were randomly split into training (66%) and validation (33%) sets. An optimal mixed effects logistic regression model was determined from validation data AUC values.
Conclusion: Quantitative indices of real-world driver data provide "ground truth" for screening and indexing phenotypes of cognitive decline, in line with ongoing efforts to link driver behavior with age-related cognitive decline and AD biomarkers. Behavioral biomarkers for diagnosing early warnings of dementia could ultimately bolster our ability to detect and intervene in early AD.

MODES OF TRANSPORTATION TO MEDICAL AND PRIMARY CARE AMONG OLDER ADULTS Zainab Suntai, Kefentse Kubanga, Emmanuel Adanu, and Abhay Lidbe, University of Alabama, Tuscaloosa, Alabama, United States
Transportation is an increasingly meaningful concern for older adults as physical, cognitive, and psychological changes in older adulthood impact mobility and accessibility. While several studies have examined the modes of transportation used among older adults, few have explored specifically how older adults are accessing primary care/medical care services. As such, this study aimed to determine the specific modes of transportation used among older adults for primary care visits. Data were derived from the 2018 National Health and Aging Trends Study (NHATS), an annual longitudinal panel survey of older adults aged 65 and older living in the United States. Descriptive analyses were conducted to examine the prevalence of several modes of access and logistic regression models were used to predict the likelihood of using the two most prevalent transportation modes, based on sociodemographic and socioeconomic factors. Results showed that 70% of older adults drive themselves to their doctor, 34.8% rely on a family member, friend, or paid person, 2.4% have a home visit, 2.1% use public transportation, 1.5% walk to their doctor and 1.1% use a taxi. Additionally, having higher income, being of younger age, being White, and having post-secondary education was associated with driving oneself to the doctor. These results indicate that while most older adults are still self-reliant on transportation to medical providers, those with lower socioeconomic status are particularly at risk of losing driving independence. Transportation-related interventions should therefore consider targeting individuals with lower economic capital by proving financial assistance, ride-share programs, and other innovative approaches.

USING CLINICAL TRIALS AS AGENTS OF TRANSFORMATION IN POPULATIONS BURDENED BY DISPARITIES Chair: Daniel Jimenez Discussant: Giyeon Kim
Older adults from racial/ethnic backgrounds as well as those from rural areas experience a disproportionate burden of physical and mental health risk factors. Given the prevalence of comorbid physical and mental health conditions in later life, the inadequacies of current treatment approaches for averting years living with disability, the disparities in access to the health care delivery system (including mental health care), and the workforce shortages to meet the mental and physical health needs of racial/ethnic and rural populations, development and testing of innovative strategies to address these disparities are of great public health significance and have the potential to change practice. This session will illustrate how four different interventions are being used to address mental and physical health needs in Latino and rural-dwelling older adults with the goal of reducing and ultimately eliminating disparities in these populations. Particular attention will be paid to the use of non-traditional interventions (e.g. social support, health promotion, technology). Results of clinical research studies will be presented alongside clinical case presentations. This integrated focus highlights the importance of adapting research interventions to real-world clinical settings.

OVERCOMING HEALTH PROMOTION BARRIERS IN RURAL HEALTH: A QUALITATIVE ANALYSIS John Batsis, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
Weight loss interventions are fraught with difficulties for older adults in rural areas due to transportation difficulties, reduced availability of staff, and lack of programs. Telemedicine can overcome these barriers. A qualitative analysis of data from 44 exit-interviews from a rural-based, older adult weight loss study, informed by thematic analysis, was conducted. Participant's age was 73 years (73% female) and BMI was 36.5kg/m2. Distance to the site was 24 miles (31 min). Key themes included: a) telemedicine can help improve one's health, is more practical than in-person visits, is less costly, and time efficient; b) the majority (60%) were initially apprehensive about using telemedicine, a fear that resolved quickly; c) setting up telemedicine was easy and acceptable, despite a quick learning curve; d) having a team member for troubleshooting was important. Using telemedicine in older adults with obesity residing in rural areas should be considered in health promotion interventions.

CERTIFIED OLDER ADULT PEER SUPPORT SPECIALISTS' USE OF TECHNOLOGY TO SUPPORT OLDER ADULTS IN THE COMMUNITY Karen Fortuna, Dartmouth College, Lebanon, New Hampshire, United States
Middle-aged and older adults with mental health conditions have a high likelihood of experiencing comorbid physical health conditions, premature nursing home admissions, and early death compared with the general population of